|Lo Seen, Danny|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/17/2000
Publication Date: N/A
Citation: N/A Interpretive Summary: A reliable estimation of plant production by Earth's ecosystems is often a prerequisite for land survey and management, while being important also in ecological and climatological studies. At a regional scale, grassland production estimates increasingly are being made using satellite data. In this paper, a modeling approach, which takes into account relevant ecosystem processes and is based on extensive field data, was used to estimate some parameters required for estimating plant production in shortgrass ecosystems. This study will help to improve the accuracy of grassland production estimates based on satellite data. This information, in turn, will improve semiarid grasslands, particularly in helping to determine adequate stocking rates. This represents a significant step toward the development of effective tools for ranchers, government agencies, and consultants for rangeland management.
Technical Abstract: A reliable estimation of primary production of terrestrial ecosystems is often a prerequisite for land survey and management, while being important also in ecological and climatological studies. At a regional scale, grassland primary production estimates are increasingly being made using satellite data. In a currently used approach, regional Gross, Net and Above-ground Net Primary Productivity (GPP, NPP and ANPP) are derived from the parametric model of Monteith and are calculated as the product of the fraction of incident photosynthetically active radiation absorbed by the canopy (fAPAR) and gross, net and above-ground net production (radiation-use) efficiencies (Eg, En, Ean); fAPAR being derived from indices calculated from satellite measured reflectances in the red and near infrared. The accuracy and realism of the primary production values estimated by this approach therefore largely depend on an accurate estimation of Eg, En, and Ean. However, data are scarce for production efficiencies of semi-arid grasslands, and their time and spatial variations are poorly documented, often leading to large errors for the estimates. In this paper, a modeling approach taking into account relevant ecosystem processes and based on extensive field data, was used to estimate time variations of Eg, En, and Ean of a shortgrass site in Arizona. These variations were explained by variations in plant water stress, temperature, leaf aging, and processes such as respiration and changes in allocation pattern between above- and below-ground compartments. Over the 3 study years, averaged values of Eg, En, and Ean were found to be 1.92, 0.74, and 0.29 g DM (MJ IPAR)-1 respectively. Eg and En exhibited large inter-annual and seasonal variations mainly